Summary
Camille Girabawe is a machine learning leader with 11 years of experience translating deep quantitative research into production ML systems; she currently leads Foundation Machine Learning for Detection Platform at Salesforce after senior ML leadership roles at Adobe and SAP. Trained as a physicist (PhD) studying synchronization in coupled chemical oscillators, she brings uncommon expertise in reaction-diffusion dynamics and microfluidics to data-driven problem solving and time-series modeling. She has a strong track record of shipping end-to-end solutions—feature engineering, scalable data pipelines, model evaluation and deployment—across multi-tenant SaaS and marketing products. Camille combines hands-on coding (Python, R, MATLAB, SQL), systems design and fabrication skills with experience in instrumentation and NI data acquisition, enabling cross-disciplinary projects that span software, hardware and experimentation. Based in the Bay Area, she pairs academic rigor with product-focused delivery and a knack for turning complex physical-system insights into robust predictive models.
11 years of coding experience
13 years of employment as a software developer
Bachelor of Science (BSc) Physics Material Science, Bachelor of Science (BSc) Physics Material Science at Kigali Institute of Science and Technology
Doctor of Philosophy (Ph.D.) Physics, Doctor of Philosophy (Ph.D.) Physics at Brandeis University